Course

面阵波束形成 两种方法 三维指向性 直接运行(Planar array beamforming methods of three-dimensional directional direct running)

The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)

说明：  PV系统模型，基于simulink的仿真(PV system model simulation based on simulink)

用MATLAB实现的一些有限元程序，共有113个(Use MATLAB to achieve some of the finite element program, a total of 113)

this is the source code for pixel value difference

有关于雷达信号的仿真和各种噪声的仿真以及信号的处理(There are on the radar signal simulation and various noise simulation, and signal processing)

genetic fuzzy (ga_fuzzy) pid gain optimal

对信道进行多种仿真，包括AWGN信道，信道参数，QAM映射方式和SFBC编码方式。(Of the channel to a variety of simulations, including the AWGN channel, channel parameters, QAM mapping method and SFBC encoding.)

Space–time block coding is a technique used in wireless communications to transmit multiple copies of a data stream across a number of antennas and to exploit the various received versions of the data to improve the reliability of data-transfer. The fact that the transmitted signal must traverse a potentially difficult environment with scattering, reflection, refraction and so on and may then be further corrupted by thermal noise in the receiver means that some of the received copies of the data will be better than others. This redundancy results in a higher chance of being able to use one or more of the received copies to correctly decode the received signal. In fact, space–time coding combines all the copies of the received signal in an optimal way to extract as much information from each of them as possible.

ica for pid design project